Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Benjamin Letham"'
Autor:
Tommi Raij, Fa-Hsuan Lin, Benjamin Letham, Kaisu Lankinen, Tapsya Nayak, Thomas Witzel, Matti Hämäläinen, Jyrki Ahveninen
Publikováno v:
Frontiers in Integrative Neuroscience, Vol 18 (2024)
Here, we report onset latencies for multisensory processing of letters in the primary auditory and visual sensory cortices. Healthy adults were presented with 300-ms visual and/or auditory letters (uppercase Roman alphabet and the corresponding audit
Externí odkaz:
https://doaj.org/article/2dce8b0465c54f1d902d8789e74ed665
Publikováno v:
PLoS ONE, Vol 11, Iss 3, p e0152316 (2016)
Type 1 interferons such as interferon-alpha (IFNα) inhibit replication of Human immunodeficiency virus (HIV-1) by upregulating the expression of genes that interfere with specific steps in the viral life cycle. This pathway thus represents a potenti
Externí odkaz:
https://doaj.org/article/c62a4a1c9d7b4c6e91839b9c937d08ba
Autor:
Benjamin Letham, Sean J. Taylor
Forecasting is a common data science task that helps organizations with capacity planning, goal setting, and anomaly detection. Despite its importance, there are serious challenges associated with producing reliable and high quality forecasts — esp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae53efa67788c4c226b97adfb1045c0a
https://doi.org/10.7287/peerj.preprints.3190v2
https://doi.org/10.7287/peerj.preprints.3190v2
Publikováno v:
Chaos (Woodbury, N.Y.). 27(6)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::340f7fc1afecf36b244fcea2af7ce228
https://pubmed.ncbi.nlm.nih.gov/27368775
https://pubmed.ncbi.nlm.nih.gov/27368775
Publikováno v:
Bayesian Anal. 14, no. 2 (2019), 495-519
Randomized experiments are the gold standard for evaluating the effects of changes to real-world systems. Data in these tests may be difficult to collect and outcomes may have high variance, resulting in potentially large measurement error. Bayesian
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8b1023194b29ac167cf362567ddd22d
Publikováno v:
MIT web domain
It is easy to find expert knowledge on the Internet on almost any topic, but obtaining a complete overview of a given topic is not always easy: information can be scattered across many sources and must be aggregated to be useful. We introduce a metho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1267f3b5dc1bce7a0434c6807ef60658
https://doi.org/10.1007/s10618-013-0329-7
https://doi.org/10.1007/s10618-013-0329-7
Publikováno v:
Ann. Appl. Stat. 9, no. 3 (2015), 1350-1371
We aim to produce predictive models that are not only accurate, but are also interpretable to human experts. Our models are decision lists, which consist of a series of if...then... statements (e.g., if high blood pressure, then stroke) that discreti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cff4d38048e6e1b0a8f91886168e4fa6
http://projecteuclid.org/euclid.aoas/1446488742
http://projecteuclid.org/euclid.aoas/1446488742
Publikováno v:
KDD
When an item goes out of stock, sales transaction data no longer reflect the original customer demand, since some customers leave with no purchase while others substitute alternative products for the one that was out of stock. Here we develop a Bayes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5511cd2358104567a9b958ce96d41fab
http://arxiv.org/abs/1502.04243
http://arxiv.org/abs/1502.04243
Publikováno v:
Chaos: An Interdisciplinary Journal of Nonlinear Science. 26:063110
Dynamical systems are frequently used to model biological systems. When these models are fit to data it is necessary to ascertain the uncertainty in the model fit. Here we present prediction deviation, a new metric of uncertainty that determines the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d73212136f077549b45c3f0b4a9babe8
https://doi.org/10.1063/1.4953795
https://doi.org/10.1063/1.4953795
Publikováno v:
MIT web domain
In sequential event prediction, we are given a "sequence database" of past event sequences to learn from, and we aim to predict the next event within a current event sequence. We focus on applications where the set of the past events has predictive p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18ed8ef1f8c47b89f70eae98cdd65098
http://hdl.handle.net/1721.1/88080
http://hdl.handle.net/1721.1/88080